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CEE 3040 Uncertainty Analysis in Engineering

Instructor: Jared Smith

Lecture: MWF 12:20-1:10pm Olin 255
Section: W 1:25-2:15pm HLS 314
W 2:30-3:20pm HLS 314
R 9:05-9:55 HLS 314
R 10:10-11:00 HLS 314
R 1:25-2:15pm HLS 314 & HLS 401

Fall.  4 credits. Student option grading.

Prerequisite: first-year calculus.      

Introduction to probability theory and statistical techniques, with examples from civil, environmental, biological, and related disciplines. Covers data presentation, commonly used probability distributions describing natural phenomena and material properties, parameter estimation, confidence
intervals, hypothesis testing, simple linear regression, and
nonparametric statistics. Examples include structural reliability, wind speed/flood distributions, pollutant concentrations, surveys and models of vehicle arrivals and other independent events.

Outcome 1: Introduce students to the basic framework provided by probability theory for analyzing problems exhibiting variability and uncertainty.

Outcome 2:   Introduce students to the basic methods and concepts employed in statistics to estimate the parameters of models, make decisions, and to describe uncertainty.

Outcome 3: Prepare students to be able to use statistical methods with confidence during their professional
careers (perhaps after further study).

Outcome 4: Encourage students to reflect on their own learning styles and educational objectives.

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